From knowledge sharing to quality performance: The role of absorptive capacity, ambidexterity and innovation capability in creative industry
Bibliographic record
Abstract
Creative industry has high contribution to the national economy. Some literature shows that creative industry does not highlight some important aspects such as knowledge sharing, absorptive capacity, and ambidexterity. The aim of this study is to analyze the relationship between knowledge sharing, absorptive capacity, ambidexterity, innovation capability and company's quality performance. This study uses mixed methods with the results of empirical study through the distribution of questionnaires to 150 business people in the creative industry and combined by interview result of creative industry entrepreneurs. The result shows that knowledge sharing had a positive and significant relationship with absorptive capacity and ambidexterity. While ambidexterity and absorptive capacity had positive and significant relationships with innovation capability and innovation capability had a positive and significant relationship with the company's quality performance. The results of this study are expected to help business people in the creative industry improve their quality performance through increased knowledge sharing, absorptive capacity, ambidexterity, and innovation capability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".